OpenRaiser/Intern-Atlas huggingface dataset:
Analisis Keamanan Protokol Secure Socket Layer (SSL) Terhadap Proses Sniffing di Jaringan
Venue: arXiv cs.CR 2015
Year: 2015

Development of information technology, especially in the field of computer network allows the exchange of information faster and more complex and the data that is exchanged can vary. Security of data on communication in the network is a major thing. Secure socket layer (SSL) is the solution to the problem, but further research on the security of the SSL protocol transactions should be done to determine the extent of SSL can secure the data on the network. When the computer sends data across the network, the data is transmitted in packets. Sniffing is a technique of monitoring of every packet traversing the network. Security threat presented by sniffers is their ability to capture all incoming and outgoing packets through the network, which includes the passwords, usernames and other sensitive issues. Packet sniffer captures the data addressed to other devices, which will then be stored for later analysis later. Sniffing can also be used by system administrators to monitor the network and solve problems in the network.
Towards Neural Network-based Reasoning
Venue: arXiv cs.AI 2015
Year: 2015

We propose Neural Reasoner, a framework for neural network-based reasoning over natural language sentences. Given a question, Neural Reasoner can infer over multiple supporting facts and find an answer to the question in specific forms. Neural Reasoner has 1) a specific interaction-pooling mechanism, allowing it to examine multiple facts, and 2) a deep architecture, allowing it to model the complicated logical relations in reasoning tasks. Assuming no particular structure exists in the question and facts, Neural Reasoner is able to accommodate different types of reasoning and different forms of language expressions. Despite the model complexity, Neural Reasoner can still be trained effectively in an end-to-end manner. Our empirical studies show that Neural Reasoner can outperform existing neural reasoning systems with remarkable margins on two difficult artificial tasks (Positional Reasoning and Path Finding) proposed in [8]. For example, it improves the accuracy on Path Finding(10K) from 33.4% [6] to over 98%.
A framework for adaptive real-time applications: the declarative real-time OSGi component model
Venue: arXiv cs.SE 2015
Year: 2015

Nowadays, more and more applications require OSGi to have some form of real-time support, which is currently very limited. The resulting closed-system solutions lack of a standard management scheme which forbids standard, system-wide policies for real-time system's deployment, adaptation, and reconfiguration. In order to tackle this problem, this paper proposes a declarative real-time component model. In this model, the distinguishing real-time contract of each component is declaratively described, and a general component real-time management interface is designed. They are used to maintain an accurate view of existing real-time components' promised contracts. A real-time component runtime service is designed to control the whole lifecycle of the components. By using global information and general control interface, it can adjust the system continue to operate without impairing the deployed components' real-time contracts in the face of run-time changes. This system allows itself to be easily extended with other constraint resolving policies to fit different context. The prototype has been tested into a simulated control system. The result shows this framework can provide good real time performance while still provides real-time component dynamicity support as well. To the best of our knowledge, this is the first comprehensive solution providing explicit real-time support from design to execution in OSGi framework.
A Practical O(R\log\log n+n) time Algorithm for Computing the Longest Common Subsequence
Venue: arXiv cs.DS 2015
Year: 2015

In this paper, we revisit the much studied LCS problem for two given sequences. Based on the algorithm of Iliopoulos and Rahman for solving the LCS problem, we have suggested 3 new improved algorithms. We first reformulate the problem in a very succinct form. The problem LCS is abstracted to an abstract data type DS on an ordered positive integer set with a special operation Update(S,x). For the two input sequences X and Y of equal length n, the first improved algorithm uses a van Emde Boas tree for DS and its time and space complexities are O(R\log\log n+n) and O(R), where R is the number of matched pairs of the two input sequences. The second algorithm uses a balanced binary search tree for DS and its time and space complexities are O(R\log L+n) and O(R), where L is the length of the longest common subsequence of X and Y. The third algorithm uses an ordered vector for DS and its time and space complexities are O(nL) and O(R).
The message does not matter: the influence of the network on information diffusion
Venue: arXiv cs.SI 2015
Year: 2015

How an information spreads throughout a social network is a valuable knowledge sought by many groups such as marketing enterprises and political parties. If they can somehow predict the impact of a given message or manipulate it in order to amplify how long it will spread, it would give them a huge advantage over their competitors. Intuitively, it is expected that two factors contribute to make an information becoming viral: how influential the person who spreads is inside its network and the content of the message. The former should have a more important role, since people will not just blindly share any content, or will they? In this work it is found that the degree of a node alone is capable of accurately predicting how many followers of the seed user will spread the information through a simple linear regression. The analysis was performed with five different messages from Twitter network that was shared with different degrees along the users. The results show evidences that no matter the content, the number of affected neighbors is predictable. The role of the content of the messages of a user is likely to influence the network formation and the path the message will follow through the network.
Iterative Thresholded Bi-Histogram Equalization for Medical Image Enhancement
Venue: arXiv cs.CV 2015
Year: 2015

Enhancement of human vision to get an insight to information content is of vital importance. The traditional histogram equalization methods have been suffering from amplified contrast with the addition of artifacts and a surprising unnatural visibility of the processed images. In order to overcome these drawbacks, this paper proposes interative, mean, and multi-threshold selection criterion with plateau limits, which consist of histogram segmentation, clipping and transformation modules. The histogram partition consists of multiple thresholding processes that divide the histogram into two parts, whereas the clipping process nicely enhances the contrast by having a check on the rate of enhancement that could be tuned. Histogram equalization to each segmented sub-histogram provides the output image with preserved brightness and enhanced contrast. Results of the present study showed that the proposed method efficiently handles the noise amplification. Further, it also preserves the brightness by retaining natural look of targeted image.
Performance Analysis of Fifth-Generation Cellular Uplink
Venue: arXiv cs.IT 2015
Year: 2015

Fifth-generation cellular networks are expected to exhibit at least three primary physical-layer differences relative to fourth-generation ones: millimeter-wave propagation, antenna-array directionality, and densification of base stations. In this paper, the effects of these differences on the performance of single-carrier frequency-domain multiple-access uplink systems with frequency hopping are assessed. A new analysis, which is much more detailed than any other in the existing literature and accommodates actual base-station topologies, captures the primary features of uplink communications. Distance-dependent power-law, shadowing, and fading models based on millimeter-wave measurements are introduced. The beneficial effects of base-station densification, highly directional sectorization, and frequency hopping are illustrated.
Tracking Federated Queries in the Linked Data
Venue: arXiv cs.DB 2015
Year: 2015

Federated query engines allow data consumers to execute queries over the federation of Linked Data (LD). However, as federated queries are decomposed into potentially thousands of subqueries distributed among SPARQL endpoints, data providers do not know federated queries, they only know subqueries they process. Consequently, unlike warehousing approaches, LD data providers have no access to secondary data. In this paper, we propose FETA (FEderated query TrAcking), a query tracking algorithm that infers Basic Graph Patterns (BGPs) processed by a federation from a shared log maintained by data providers. Concurrent execution of thousand subqueries generated by multiple federated query engines makes the query tracking process challenging and uncertain. Experiments with Anapsid show that FETA is able to extract BGPs which, even in a worst case scenario, contain BGPs of original queries.
F2- Rules for Qualification of Developing and Managing Software Product Line
Venue: arXiv cs.SE 2015
Year: 2015

Software product line has emerged as a valuable concept of developing software based on reusable software assets. The concept aims on effective utilization of software assets, reduced time to delivery, improved quality and better benefits to cost ratio of products. In this paper we have defined certain rules for the qualification of developing and managing a software product line. An organization must follow these rules in order to establish and manage software product line effectively.
Multiple kernel multivariate performance learning using cutting plane algorithm
Venue: arXiv cs.LG 2015
Year: 2015

In this paper, we propose a multi-kernel classifier learning algorithm to optimize a given nonlinear and nonsmoonth multivariate classifier performance measure. Moreover, to solve the problem of kernel function selection and kernel parameter tuning, we proposed to construct an optimal kernel by weighted linear combination of some candidate kernels. The learning of the classifier parameter and the kernel weight are unified in a single objective function considering to minimize the upper boundary of the given multivariate performance measure. The objective function is optimized with regard to classifier parameter and kernel weight alternately in an iterative algorithm by using cutting plane algorithm. The developed algorithm is evaluated on two different pattern classification methods with regard to various multivariate performance measure optimization problems. The experiment results show the proposed algorithm outperforms the competing methods.
Compressed Sensing and Reconstruction of Unstructured Mesh Datasets
Venue: arXiv cs.IT 2015
Year: 2015

Exascale computing promises quantities of data too large to efficiently store and transfer across networks in order to be able to analyze and visualize the results. We investigate Compressive Sensing (CS) as a way to reduce the size of the data as it is being stored. CS works by sampling the data on the computational cluster within an alternative function space such as wavelet bases, and then reconstructing back to the original space on visualization platforms. While much work has gone into exploring CS on structured data sets, such as image data, we investigate its usefulness for point clouds such as unstructured mesh datasets found in many finite element simulations. We sample using second generation wavelets (SGW) and reconstruct using the Stagewise Orthogonal Matching Pursuit (StOMP) algorithm. We analyze the compression ratios achievable and quality of reconstructed results at each compression rate. We are able to achieve compression ratios between 10 and 30 on moderate size datasets with minimal visual deterioration as a result of the lossy compression.
Prepartition: Paradigm for the Load Balance of Virtual Machine Allocation in Data Centers
Venue: arXiv cs.DC 2015
Year: 2015

It is significant to apply load-balancing strategy to improve the performance and reliability of resource in data centers. One of the challenging scheduling problems in Cloud data centers is to take the allocation and migration of reconfigurable virtual machines (VMs) as well as the integrated features of hosting physical machines (PMs) into consideration. In the reservation model, the workload of data centers has fixed process interval characteristics. In general, load-balance scheduling is NP-hard problem as proved in many open literatures. Traditionally, for offline load balance without migration, one of the best approaches is LPT (Longest Process Time first), which is well known to have approximation ratio 4/3. With virtualization, reactive (post) migration of VMs after allocation is one popular way for load balance and traffic consolidation. However, reactive migration has difficulty to reach predefined load balance objectives, and may cause interruption and instability of service and other associated costs. In view of this, we propose a new paradigm, called Prepartition, it proactively sets process-time bound for each request on each PM and prepares in advance to migrate VMs to achieve the predefined balance goal. Prepartition can reduce process time by preparing VM migration in advance and therefore reduce instability and achieve better load balance as desired. We also apply the Prepartition to online (PrepartitionOn) load balance and compare it with existing online scheduling algorithms. Both theoretical and experimental results are provided.
DSA Security Enhancement through Efficient Nonce Generation
Venue: arXiv cs.CR 2015
Year: 2015

The Digital Signature Algorithm (DSA) has become the de facto standard for authentication of transacting entities since its inception as a standard by NIST. An integral part of the signing process in DSA is the generation of a random number called a nonce or an ephemeral key. If sufficient caution is not taken while generating the nonce, it can lead to the discovery of the private-key paving the way for critical security violations further on. The standard algorithms for generation of the nonce as specified by NIST, as well as the widely implemented random number generators, fail to serve as true random sources, thus leaving the DSA algorithm open to attack, resulting in possible signature forgery in electronic transactions, by potential attackers. Furthermore, the user can select the nonce arbitrarily, which leads to a subliminal channel being present to exchange messages through each signature, which may be intolerable for security reasons. In this paper, we have improved the security of the DSA algorithm by proposing an efficient nonce-generation process, which ensures that the generated nonce is sufficiently random as well as unique for each generated signature, thereby securing the signing process. Furthermore, our algorithm also ensures that there are no subliminal channels present in DSA.
A Logical Approach to Event Handling in Imperative Languages
Venue: arXiv cs.PL 2015
Year: 2015

While event handling is a key element in modern interactive programming, it is unfortunate that its theoretical foundation is rather weak. To solve this problem, we propose to adopt a game-logical approach of computability logic \cite{Jap08} to event handling.
Efficient Large-scale Trace Checking Using MapReduce
Venue: arXiv cs.SE 2015
Year: 2015

The problem of checking a logged event trace against a temporal logic specification arises in many practical cases. Unfortunately, known algorithms for an expressive logic like MTL (Metric Temporal Logic) do not scale with respect to two crucial dimensions: the length of the trace and the size of the time interval for which logged events must be buffered to check satisfaction of the specification. The former issue can be addressed by distributed and parallel trace checking algorithms that can take advantage of modern cloud computing and programming frameworks like MapReduce. Still, the latter issue remains open with current state-of-the-art approaches. In this paper we address this memory scalability issue by proposing a new semantics for MTL, called lazy semantics. This semantics can evaluate temporal formulae and boolean combinations of temporal-only formulae at any arbitrary time instant. We prove that lazy semantics is more expressive than standard point-based semantics and that it can be used as a basis for a correct parametric decomposition of any MTL formula into an equivalent one with smaller, bounded time intervals. We use lazy semantics to extend our previous distributed trace checking algorithm for MTL. We evaluate the proposed algorithm in terms of memory scalability and time/memory tradeoffs.
Using Genetic Algorithms to Benchmark the Cloud
Venue: arXiv cs.DC 2015
Year: 2015

This paper presents a novel application of Genetic Algorithms(GAs) to quantify the performance of Platform as a Service (PaaS), a cloud service model that plays a critical role in both industry and academia. While Cloud benchmarks are not new, in this novel concept, the authors use a GA to take advantage of the elasticity in Cloud services in a graceful manner that was not previously possible. Using Google App Engine, Heroku, and Python Anywhere with three distinct classes of client computers running our GA codebase, we quantified the completion time for application of the GA to search for the parameters of controllers for dynamical systems. Our results show statistically significant differences in PaaS performance by vendor, and also that the performance of the PaaS performance is dependent upon the client that uses it. Results also show the effectiveness of our GA in determining the level of service of PaaS providers, and for determining if the level of service of one PaaS vendor is repeatable with another. Such a concept could then increase the appeal of PaaS Cloud services by making them more financially appealing.
Comparing Deadlock-Free Session Typed Processes
Venue: arXiv cs.LO 2015
Year: 2015

Besides respecting prescribed protocols, communication-centric systems should never "get stuck". This requirement has been expressed by liveness properties such as progress or (dead)lock freedom. Several typing disciplines that ensure these properties for mobile processes have been proposed. Unfortunately, very little is known about the precise relationship between these disciplines--and the classes of typed processes they induce. In this paper, we compare L and K, two classes of deadlock-free, session typed concurrent processes. The class L stands out for its canonicity: it results naturally from interpretations of linear logic propositions as session types. The class K, obtained by encoding session types into Kobayashi's usage types, includes processes not typable in other type systems. We show that L is strictly included in K. We also identify the precise condition under which L and K coincide. One key observation is that the degree of sharing between parallel processes determines a new expressiveness hierarchy for typed processes. We also provide a type-preserving rewriting procedure of processes in K into processes in L. This procedure suggests that, while effective, the degree of sharing is a rather subtle criteria for distinguishing typed processes.
Analysing and Comparing Encodability Criteria
Venue: arXiv cs.LO 2015
Year: 2015

Encodings or the proof of their absence are the main way to compare process calculi. To analyse the quality of encodings and to rule out trivial or meaningless encodings, they are augmented with quality criteria. There exists a bunch of different criteria and different variants of criteria in order to reason in different settings. This leads to incomparable results. Moreover it is not always clear whether the criteria used to obtain a result in a particular setting do indeed fit to this setting. We show how to formally reason about and compare encodability criteria by mapping them on requirements on a relation between source and target terms that is induced by the encoding function. In particular we analyse the common criteria full abstraction, operational correspondence, divergence reflection, success sensitiveness, and respect of barbs; e.g. we analyse the exact nature of the simulation relation (coupled simulation versus bisimulation) that is induced by different variants of operational correspondence. This way we reduce the problem of analysing or comparing encodability criteria to the better understood problem of comparing relations on processes.
Encoding CSP into CCS
Venue: arXiv cs.LO 2015
Year: 2015

We study encodings from CSP into asynchronous CCS with name passing and matching, so in fact, the asynchronous pi-calculus. By doing so, we discuss two different ways to map the multi-way synchronisation mechanism of CSP into the two-way synchronisation mechanism of CCS. Both encodings satisfy the criteria of Gorla except for compositionality, as both use an additional top-level context. Following the work of Parrow and Sjödin, the first encoding uses a centralised coordinator and establishes a variant of weak bisimilarity between source terms and their translations. The second encoding is decentralised, and thus more efficient, but ensures only a form of coupled similarity between source terms and their translations.
Algebraic Local Cohomology with Parameters and Parametric Standard Bases for Zero-Dimensional Ideals
Venue: arXiv cs.SC 2015
Year: 2015

A computation method of algebraic local cohomology with parameters, associated with zero-dimensional ideal with parameter, is introduced. This computation method gives us in particular a decomposition of the parameter space depending on the structure of algebraic local cohomology classes. This decomposition informs us several properties of input ideals and the output of our algorithm completely describes the multiplicity structure of input ideals. An efficient algorithm for computing a parametric standard basis of a given zero-dimensional ideal, with respect to an arbitrary local term order, is also described as an application of the computation method. The algorithm can always output "reduced" standard basis of a given zero-dimensional ideal, even if the zero-dimensional ideal has parameters.
The Depth-Restricted Rectilinear Steiner Arborescence Problem is NP-complete
Venue: arXiv cs.CC 2015
Year: 2015

In the rectilinear Steiner arborescence problem the task is to build a shortest rectilinear Steiner tree connecting a given root and a set of terminals which are placed in the plane such that all root-terminal-paths are shortest paths. This problem is known to be NP-hard. In this paper we consider a more restricted version of this problem. In our case we have a depth restrictions $d(t)\in\mathbb{N}$ for every terminal $t$. We are looking for a shortest binary rectilinear Steiner arborescence such that each terminal $t$ is at depth $d(t)$, that is, there are exactly $d(t)$ Steiner points on the unique root-$t$-path is exactly $d(t)$. We prove that even this restricted version is NP-hard.